Yes, most of us work in Technology companies those advise many organizations globally for taking technological decision and encourage them to use the latest and advanced technologies to automate their operations. However, how many of those companies are using technology within their organizations and drive innovations for their internal requirements. Both the employees and employers are suffering because a proper system is not in place for solving the problems like Lack of effective appraisal system, identifying the right resources for the projects, unable to stop the talent leaving the organization etc. Let’s look at those and how we can try to solve using the technologies like Machine Learning(ML) and Artificial Intelligence(AI). Yes, we are in the world of Machine Learning(ML) and Artificial Intelligence (AI) and we must now start thinking about using them effectively.
Undoubtedly, the future is data driven but most of the current problems are due to lack of proper data available for decision making. The world is changing faster so is the technology, there is a huge requirement for resource with latest skills. It is really a big challenge for the larger organizations to find right resource, they mostly depend on their manager’s input which is not always driven by good data. Result of this, organization invest on wrong resources and right resources leave the company. So how do we solve such issues?
First thing we need to use well integrated IT system in place which exchange the data between systems. These data need to be stored in the structured way so that every other system can pull th data effectively. Additionally, we need to gather the data from the employees, managers, leaders and other systems. We can use AI to ask more personalized questions effectively and use ML to reach to conclusions.
Confused? Let’s get down to the details.
According to me, we need to maintain minimum of below data for the processing. Many organizations maintain some of those data but in most cases, those are not very effective to be used across multiple systems and it would stay forever but not usable.
- Individual Development Plan (IDP) – provides data of each employees on short and long-term aspirations.
- Skills Acquired – provides current skills and how quick has he/she acquired skills. It also helps us make some predictions as well.
- Earned Certification – Provides current certification and how open he/she is to do new certifications.
- Periodic employee survey results – It is very important that we effectively do this survey, ask relevant questions and may use AI to ask more questions based on the data available and answers provided. It also would provide trending data on what is it really want to learn and do.
- Skills requirement – provides each team current requirement and future requirements.
- Probability of passing percentage – provides data on how many employees should be targeted to get required number of certifications.
Process this data and feed into good training dataset models those can predict the results that you wanted. You may use AI to do the more personalized surveys from the employees and leadership to keep feeding the ML because more data is always good. Also, you can use Big data to handle large data and get some industry trends to support your decision making. Similar approach can be used for doing appraisals as well rather than using some of the traditional approaches those are not effective. Appraisal system must get a larger view than identifying better guy from smaller team. It should be able to evaluate the employees across the organization and rate them.
Let’s change the traditional methods and use our existing workforce effectively to drive success. We need to think out of the box, bring innovation, invite ideas and grow faster.
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